Triple
T22118727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canarsie Line |
E546606
|
entity |
| Predicate | wasFirstNYCLineWith |
P147061
|
FINISHED |
| Object | full-line CBTC operation |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: full-line CBTC operation | Statement: [Canarsie Line, wasFirstNYCLineWith, full-line CBTC operation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasFirstNYCLineWith Context triple: [Canarsie Line, wasFirstNYCLineWith, full-line CBTC operation]
-
A.
oldestSubwayLineIn
Indicates that a subway line is the earliest-built or longest-operating subway line within a specified geographic area or transit system.
-
B.
isFirstMetroLineInCity
Indicates that a metro line is the earliest or original metro line established in a given city.
-
C.
firstSubwayOpeningDate
Indicates the calendar date on which a subway system or line first began operating.
-
D.
bronxLine
Indicates a relationship where something is part of, associated with, or runs along the Bronx transit or route line.
-
E.
primaryManhattanLine
Indicates that one line segment or path is the main or dominant axis, measured using Manhattan (grid-based) distance, relative to other possible lines.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294fcf2c81909b610e03a0f1921f |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:31 p.m.